Hacker News Reader

While i agree that it is more difficult to distribute computational load between cpu and gpu than it aught to be, Gpu is not necessary faster for all workloads than cpu, it is very specific. Most of computations can probably be executex faster on cpu.

View on HN

agreed, but i take the GP's argument to be that the languages aren't sufficiently expressive to allow us to communicate generically about workloads in a way that allows a system to correctly determine whether they would be faster on a CPU or not.

Correct. Another good example here is that to my knowledge, developers don't do things like write directly to L1, L2, L3... they tune so that those caches are used effectively.

Reply on news.ycombinator.com